Pepino mosaic virus genotype shift in North America and development of a loop-mediated isothermal amplification for rapid genotype identification
Bibliographic record
Abstract
BACKGROUND: Pepino mosaic, once an emerging disease a decade ago, has become endemic on greenhouse tomatoes worldwide in recent years. Three distinct genotypes of Pepino mosaic virus (PepMV), including EU, US1 and CH2 have been recognized. Our earlier study conducted in 2006-2007 demonstrated a predominant EU genotype in Canada and United States. The objective of the present study was to monitor the dynamic of PepMV genetic composition and its current status in North America. RESULTS: Through yearly monitoring efforts in 2009-2012, we detected a dramatic shift in the prevalent genotype of PepMV from the genotype EU to CH2 in North America since early 2010, with another shift from CH2 to US1 occurring in Mexico only two years later. Through genetic diversity analysis using the coat protein gene, such genotype shifting of PepMV in North America was linked to the positive identification of similar sequence variants in two different commercial tomato seed sources used for scion and rootstock, respectively. To allow for a quick identification, a reverse transcription loop-mediated isothermal amplification (RT-LAMP) system was developed and demonstrated to achieve a rapid identification for each of the three genotypes of PepMV, EU, US1 and CH2. CONCLUSION: Through systemic yearly monitoring and genetic diversity analysis, we identified a linkage between the field epidemic isolates and those from commercial tomato seed lots as the likely sources of initial PepMV inoculum that resulted in genetic shifting as observed on greenhouse tomatoes in North America. Application of the genotype-specific RT-LAMP system would allow growers to efficiently determine the genetic diversity on their crops.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".